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Publisher: SpringernatureWoS Q: Q3

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    Article
    Citation - WoS: 2
    Citation - Scopus: 3
    Irisin Pathways in Hearts of Type 1 Diabetic Adult Male Rats Following 6 Weeks of Moderate and High-Volume Aerobic Exercise on a Treadmill
    (Springernature, 2023) Celik, Humeyra; Dursun, Ali Dogan; Tatar, Yakup; Omercioglu, Goktug; Bastug, Metin
    Purpose Exercise-mediated protection from cardiomyopathy in diabetes through myokines raises the question of what volume of exercise should be performed. Irisin pathway molecules (consisting of peroxisome proliferator-activated receptor gamma coactivator 1-alpha (PGC-1 alpha), irisin, peroxisome proliferator-activated receptors-alpha (PPAR-alpha) and uncoupling protein 1 (UCP1)), which have been shown to be mostly expressed in the heart, are thought to have beneficial effects on diabetic heart. The aim of the study is to evaluate the effects of different exercise protocols on irisin pathway in Type 1 diabetic heart. Methods Diabetic (60 mg/kg streptozotocin i.p.) and healthy Wistar Albino rats (n = 60) were trained under moderate and high-volume exercise protocols on rat treadmill for 6 weeks. After killing, mRNA transcript and protein abundance of PGC-1 alpha, irisin, PPAR-alpha, and UCP1 were determined in the left ventricles of healthy and diabetic rats. Results PPAR-alpha, FNDC5, and UCP1 mRNA levels increased significantly in healthy moderate-volume exercise group (HMVE) compared to healthy high-volume exercise (HHVE) and diabetic moderate-volume exercise groups (DMVE). Moreover, protein levels of irisin and UCP1 also elevated significantly in the diabetic high-volume exercise group (DHVE) compared to the healthy control group (HC), although there was no significant difference between the groups in PPAR-alpha. Conclusion Irisin and UCP1 protein values increased due to HHEV in the heart of Type 1 diabetic rats, but PPAR-alpha values did not change; it shows that HHEV is suitable for the heart of Type 1 diabetic rats in terms of the benefits of the pathway of irisin.
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    Review
    Citation - WoS: 28
    Citation - Scopus: 22
    Enhanced Selex Platforms for Aptamer Selection With Improved Characteristics: a Review
    (Springernature, 2024) Didarian, Reza; Ozbek, Hatice K.; Ozalp, Veli C.; Erel, Ozcan; Yildirim-Tirgil, Nimet
    This review delves into the advancements in molecular recognition through enhanced SELEX (Systematic Evolution of Ligands by Exponential Enrichment) platforms and post-aptamer modifications. Aptamers, with their superior specificity and affinity compared to antibodies, are central to this discussion. Despite the advantages of the SELEX process-encompassing stages like ssDNA library preparation, incubation, separation, and PCR amplification-it faces challenges, such as nuclease susceptibility. To address these issues and propel aptamer technology forward, we examine next-generation SELEX platforms, including microfluidic-based SELEX, capillary electrophoresis SELEX, cell-based aptamer selection, counter-SELEX, in vivo SELEX, and high-throughput sequencing SELEX, highlighting their respective merits and innovations. Furthermore, this article underscores the significance of post-aptamer modifications, particularly chemical strategies that enhance aptamer stability, reduce renal filtration, and expand their target range, thereby broadening their utility in diagnostics, therapeutics, and nanotechnology. By synthesizing these advanced SELEX platforms and modifications, this review illuminates the dynamic progress in aptamer research and outlines the ongoing efforts to surmount existing challenges and enhance their clinical applicability, charting a path for future breakthroughs in this evolving field.
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    Article
    Afthd: Bayesian Accelerated Failure Time Model for High-Dimensional Time-To Data
    (Springernature, 2025) Kumari, Pragya; Bhattacharjee, Atanu; Vishwakarma, Gajendra K.; Tank, Fatih
    Analyzing high-dimensional (HD) data with time-to-event outcomes poses a formidable challenge. The accelerated failure time (AFT) model, an alternative to the Cox proportional hazard model in survival analysis, lacks sufficient R packages for HD time-to-event data under the Bayesian paradigm. To address this gap, we develop the R package afthd. This tool facilitates advanced AFT modeling, offering Bayesian analysis for univariate and multivariable scenarios. This work includes diagnostic plots and an open-source R code for working with HD data, extending the conventional AFT model to the Bayesian framework of log-normal, Weibull, and log-logistic AFT models. The methodology is rigorously validated through simulation techniques, yielding consistent results across parametric AFT models. The application part is also performed on two different real HD liver cancer datasets, which reveals the proposed method's significance by obtaining inferences for survival estimates for the disease. Our developed package afthd is competent in working with HD time-to-event data using the conventional AFT model along with the Bayesian paradigm. Other aspects, like missing values in covariates within HD data and competing risk analysis, are also covered in this article.